The great transformation of e-learning during the Covid-19 pandemic has led to the emergence of new learning tools and virtual learning environments through Internet. Despite many advantages of e-Learning courseware systems such as availability, flexibility and accessibility, students of some sectors such as engineering, science and technology are facing several limitations in conducting their practical works remotely through online platform for laboratory experiments. The specific objective of this study was to come up with an updated success criteria and list of requirements that should be considered for developing a sustainable artificial intelligence-based online laboratory courseware system. Data for this study were collected using online questionnaire distributed to a group of e-Learning experts. NVivo software was used to analyze experts’ comments on how to construct the online laboratory courseware systems. This research revealed 16 basic design and development criteria for the online laboratory courseware system, which are distributed into eight sub-branches and organized into four primary aspects. These findings suggest that in general 30 accurate indicators for the design of an effective laboratory learning system (LLS) for engineering, science and technology sectors dealing with content management, assessment, accessibility and usability as well as the adoption of artificial intelligence techniques.

This Full-Length Research Paper deals with the effectiveness of training using educational robots on developing various skills for metacognitive thinking and engagement. Educational Robotics (ER) is a subject that aims to introduce children to robotics and programming through hands-on activities starting at a young age. There is evidence that ER plays a crucial role in enhancing students' academic achievement, cognitive abilities, and programming skills. Despite the growing interest in implementing ER to promote learning outcomes, there has been far too little focus on demonstrating ER effects on the development of certain types of thinking abilities (e.g. reflective thinking), and social skills that include engagement and its pedagogical implications. This study aims to evaluate the effects of ER on STEM students' engagement and reflective thinking. A sample of 24 middle school students (age range: 11–13 years) took part in an intensive ER-Lab for 6 sessions (3 weeks) by using open-source hardware and software kits through articulated robots and mobile robots. The research data in this study are drawn from two main sources on a five-point Likert scale: engagement questionnaire, and reflective thinking scale. The results of this investigation showed that students keep pleasure experience interacting and performing robotics activities. The results also showed a remarkable superiority of the students' reflective thinking skills on the dimensions (habitual action, understanding, reflection, and critical reflection). Students reflected their expectations and challenges after ER training with sets of recommendations accordingly. This study contributes to robotics' STEM education by expanding the scope of prior research to provide evidence of ER impact on 21st-century skills, particularly, reflective thinking skills. Based on the study's findings, we suggest developing robotic activities in different ER learning scenarios for a better understanding of the engagement processes. We recommend expanding the pedagogical possibilities of ER in improving extensive thinking skills, adaptation, and encouraging socialization and collaboration. This encourages exploring the feedback, reflection, and needs of the teachers and parents in terms of the impact of ER training on students thinking skills.

The growing adoption of learning analytics (LA) approaches and data mining (DM) techniques using educational gamification data sets is reflected in increased publications on this topic. However, with different gamified contexts and a variety of LA methods available, no comprehensive review summarized the obtained findings. Therefore, this research aims to identify studies’ characteristics, objectives, and methods used in gamification learning analytics (GaLA) research. To identify these, this study comprehensively reviewed the literature of 24 studies selected from an initial pool of 221 search results. The findings show that GaLA methods can be categorized into: visualization, data mining, social network analysis (SNA), statistics, and correlations. In conclusion, GaLA is defined as a data-driven approach using various methods of data analysis and mining techniques in gamified contexts for collecting, analyzing, and reporting data to assess or enhance the gameful experience, understand student behaviour, and improve learning outcomes.

Many students suffer from a lack of motivation and interest in doing their homework. This paper introduced a micro-design approach for implementing gamification of learning assignments, led to the extraction of the procedures for gamifying assignment with the micro-design approach, and a suggested conceptual design model called “Snowflake”. The most interesting finding was that micro-level analysis has a positive impact on a gamified assignment which begins with the identification of raw objects such as quizzes, lessons, learning objects and resources.

Massive Open Online Courses (MOOCs) have a remarkable ability to expand access to a large scale of participants worldwide, beyond the formality of the higher education systems. MOOCs support participants to be actively involved in collaborative learning and construct their own learning experience in a variety of domains. However, one of the biggest challenges facing MOOCs is how to assess the learners’ performance in a massive learning environment beyond traditional automated assessment methods. To address this challenge, peer assessment has been proposed as an effective assessment method in MOOCs. The problem is, however, how to ensure the quality of the peer assessment in terms of validity and reliability. Moreover, assessment in blended MOOCs (bMOOCs) introduces unique challenges regarding the best peer assessment model in a learning environment that brings together face-to-face interactions and online activities. This paper presents the details of a study conducted to investigate peer assessment in bMOOCs. The study results show that flexible rubrics have the potential to make the feedback process more accurate, credible, transparent, valid, and reliable, thus ensuring the quality of the peer assessment task.

Massive Open Online Courses (MOOCs) have gained a lot of attention in the last years as a new technology enhanced learning (TEL) approach in higher education. MOOCs provide more educational opportunities to a massive number of learners to attend free online courses around the globe. Discussions around MOOCs have been focusing on the potential, social, institutional, technological, relevance, and marketing issues and less on the quality design of MOOC environments. Several studies have reported a high drop-out rate in average of 95% of course participants and other pedagogical problems concerning assessment and feedback. Thus, the quality of MOOCs design is worth additional investigation. Although several studies identified a large set of criteria to the successful design of TEL systems in general, not all of them can be used in the MOOC context, due to some unique features of MOOCs. This study is a first step towards identifying specific criteria that need to be considered when designing and implementing MOOCs. The results of this empirical study are based on a large survey targeting learners as well as professors, both with MOOC experience. As a result, we identified and rated 74 indicators classified into our two main dimensions of pedagogical and technological criteria distributed over six categories. From these, the learning analytics and assessment categories were found to be the key features for effective MOOCs.

Social communication tools in E-Learning have seen monumental growth in the last decade. Blogs as one of the most important tools have a huge contribution in social communication in Learning Management Systems (LMS), and the majority of research incorporating blogs in LMS reveals the effectivity of them. Thus, the quality of blog design becomes the main factor that determines the success of educational blogs. Although a literature review of guidelines and web page standards contain a variety of categories to cover most features of web page design, not all of them can be used to create an effective blog. There is a need to further explore these technologies in educational contexts and identify the criteria of combining them in unit design. The main purpose of this paper is identifying the educational blogs criteria by analysing the literature, research and the reviews of experts in the field. The study outcomes include the final list of blogs criteria which are classified into 6 categories and 80 indicators.